Function reference • polmineR

Package Basics Getting started with polmineR (CLI And GUI usage).
`polmineR()`	polmineR-package
`get_info()` `show_info()`	Generic methods defined in the polmineR package
Corpora and subcorpora Corpora, subcorpora/partitions, and partition_bundle objects are the point of departure for any analysis using polmineR. Constructors introduced in the next section require an understanding of basic methods and classes to generate and manage (sub-)corpora
`use()`	Add corpora in R data packages to session registry.
`corpus(<character>)` `corpus(<missing>)`	Corpus class initialization
`name(<corpus>)` `get_corpus(<corpus>)` `show(<corpus>)` `$`(<corpus>) `get_info(<corpus>)` `show_info(<corpus>)`	Corpus class methods
`subset(<corpus>)` `subset(<character>)` `subset(<subcorpus>)` `subset(<remote_corpus>)`	Subsetting corpora and subcorpora
`ocpu_exec()`	Execute code on OpenCPU server
`aggregate(<slice>)`	Virtual class slice.
`partition()`	Initialize a partition.
`partition_bundle()`	Generate bundle of partitions.
`p_attributes()`	Get p-attributes.
`s_attributes()`	Get s-attributes.
`as.speeches()`	Split corpus or partition into speeches.
`summary(<subcorpus>)` `name<-`(<subcorpus>) `get_corpus(<subcorpus>)` `size(<subcorpus>)`	The S4 subcorpus class.
`show(<subcorpus_bundle>)` `merge(<subcorpus_bundle>)` `merge(<subcorpus>)` `split(<subcorpus>)` `split(<corpus>)` `split(<subcorpus_bundle>)`	Bundled subcorpora
`as.regions()` `as.data.table(<regions>)`	Regions of a CWB corpus.
Methods I: Basic Vocabulary Data analysis using polmineR will usually start by calling a constructor method resulting in an S4 class object with the name of the calling method. All methods basic vocabulary can be applied to corpora (defined by a character vector), to partitions, and to partition_bundle objects, some are applicable to additional classes. These methods are designed to be used in a pipe.
`kwic()`	Perform keyword-in-context (KWIC) analysis.
`hits()`	Get hits for query
`count()`	Get counts.
`dispersion()`	Dispersion of a query or multiple queries.
`ngrams()`	Get N-Grams
`context()`	Analyze context of a node word.
`cooccurrences()`	Get cooccurrence statistics.
`features()`	Get features by comparison.
`as.phrases(<ngrams>)` `as.phrases(<matrix>)` `as.character(<phrases>)` `concatenate_phrases()`	Manage and use phrases
Methods II: Processing Objects The polmineR package offers a repertoire to modify base objects, and for type conversion. Methods for modyfing classes and type conversion.
`size()`	Get Number of Tokens.
`terms(<slice>)` `terms(<partition>)` `terms(<subcorpus>)` `terms(<character>)`	Get terms in `partition` or corpus.
`enrich()`	Enrich an object.
`trim()` `punctuation`	trim an object
`noise()`	detect noise
`encoding()` `encoding<-`()	Get and set encoding.
`as.TermDocumentMatrix()` `as.DocumentTermMatrix()`	Generate TermDocumentMatrix / DocumentTermMatrix.
`as.sparseMatrix()`	Type conversion - get sparseMatrix.
`as.VCorpus(<partition_bundle>)`	Get VCorpus.
`chisquare()`	Perform chisquare-text.
`ll()`	Compute Log-likelihood Statistics.
`t_test()`	Perform t-test.
`pmi()`	Calculate Pointwise Mutual Information (PMI).
`means()`	calculate means
`weigh()`	Apply Weight to Matrix
`store()` `mail()` `browse()`	Defunct functionality
`dotplot()`	dotplot
`restore()`	Restore S4 object with data.table slots
Methods III: Fulltext Output A key consideration of polmineR is to combine quantitative and qualitative steps of analysis in a workflow. A set of methods is exposed to generate and enhance fulltext output.
`read()`	Display full text.
`html()`	Generate html from object.
`annotations()` `annotations<-`() `edit(<textstat>)`	Annotation functionality
`as.markdown()`	Get markdown-formatted full text of a partition.
`store()` `mail()` `browse()`	Defunct functionality
`view()`	Inspect object using View().
`highlight()`	Highlight tokens in text output.
`tooltips()`	Add tooltips to text output.
`get_template()`	Get template for reconstructing full text.
`get_type()`	Get corpus/partition type.
`partition_to_string`	Decode as String.
The 'textstat' Class & Childs The main feature of the textstat class and of classes inheriting from it is that it keeps statistical information about a corpus or partition in a data.table in the field ‘stat’. Methods defined for the textstat superclass are available for its child classes, unless they are overloaded in a specified manner.
`name(<textstat>)` `name(<character>)` `name<-`(<textstat>) `round(<textstat>)` `sort(<textstat>)` `as.bundle()` `+`(<textstat>,<textstat>) `subset(<textstat>)` `as.data.table(<textstat>)` `show(<textstat>)` `p_attributes(<textstat>)` `knit_print(<textstat>)` `get_corpus(<textstat>)` `format(<textstat>)` `view(<textstat>)`	S4 textstat superclass.
`summary(<count>)` `length(<count>)` `hist(<count>)`	Count class.
`ngrams_class`	Ngrams class.
`p_attributes(<partition>)` `p_attributes(<subcorpus>)` `is.partition()` `enrich(<partition>)` `as.regions(<partition>)` `split(<partition>)`	Partition class and methods.
`sample(<hits>)`	Hits class.
`length(<context>)` `p_attributes(<context>)` `count(<context>)` `sample(<context>)` `enrich(<context>)` `as.regions(<context>)` `trim(<context>)`	Context class.
`show(<cooccurrences>)` `as.data.frame(<cooccurrences_bundle>)` `format(<cooccurrences>)` `view(<cooccurrences>)` `view(<cooccurrences_reshaped>)`	Cooccurrences class.
`as.simple_triplet_matrix(<Cooccurrences>)` `as_igraph(<Cooccurrences>)` `subset(<Cooccurrences>)` `decode(<Cooccurrences>)` `kwic(<Cooccurrences>)` `as.sparseMatrix(<Cooccurrences>)` `enrich(<Cooccurrences>)`	Cooccurrences class for corpus/partition.
`Cooccurrences(<corpus>)` `Cooccurrences(<character>)` `Cooccurrences(<slice>)` `Cooccurrences(<partition>)` `Cooccurrences(<subcorpus>)`	Get all cooccurrences in corpus/partition.
`summary(<features>)` `show(<features>)` `summary(<features_bundle>)` `format(<features>)` `view(<features>)`	Feature selection by comparison.
The 'kwic' & 'Labels' Classes xxx
`get_corpus(<kwic>)` `count(<kwic>)` `as.DocumentTermMatrix(<kwic>)` `as.TermDocumentMatrix(<kwic>)` `show(<kwic>)` `knit_print(<kwic>)` `as.character(<kwic>)` `[`(<kwic>,<ANY>,<ANY>,<ANY>) `subset(<kwic>)` `as.data.frame(<kwic>)` `length(<kwic>)` `sample(<kwic>)` `merge(<kwic_bundle>)` `enrich(<kwic>)` `format(<kwic>)` `view(<kwic>)`	S4 kwic class
The 'bundle' Class & Childs S4 classes for managing text analysis.
`name<-`(<bundle>) `length(<bundle>)` `names(<bundle>)` `names<-`(<bundle>,<vector>) `unique(<bundle>)` `+`(<bundle>,<bundle>) `+`(<bundle>,<textstat>) `[[`(<bundle>) `[[<-`(<bundle>) `$`(<bundle>) `$<-`(<bundle>) `sample(<bundle>)` `as.bundle(<list>)` `as.bundle(<textstat>)` `as.data.table(<bundle>)` `as.matrix(<bundle>)` `subset(<bundle>)` `as.list(<bundle>)` `as.list(<bundle>)` `get_corpus(<bundle>)`	Bundle Class
`show(<partition_bundle>)` `summary(<partition_bundle>)` `merge(<partition_bundle>)` `[`(<partition_bundle>,<ANY>,<ANY>,<ANY>) `barplot(<partition_bundle>)` `as.partition_bundle(<list>)` `partition_bundle(<environment>)` `enrich(<partition_bundle>)` `s_attributes(<partition_bundle>)` `flatten()`	Bundle of partitions (partition_bundle class).
`context_bundle-class`	S4 context_bundle class
`blapply()`	apply a function over a list or bundle
Low-level CWB Access The API used to access CWB indexed corpora is the RcppCWB package. A set of functions in the polmineR package serves as an intermediate interface to access corpus data.
`registry_move()` `registry()` `data_dir()`	Get registry and data directories.
`registry_reset()`	Reset registry directory.
`registry_get_name()` `registry_get_id()` `registry_get_home()` `registry_get_info()` `registry_get_encoding()` `registry_get_p_attributes()` `registry_get_s_attributes()` `registry_get_properties()`	Evaluate registry file.
`cpos()`	Get corpus positions for a query or queries.
`get_token_stream()`	Get Token Stream.
`decode()`	Decode corpus or subcorpus.
`is.cqp()` `check_cqp_query()` `as.cqp()`	Tools for CQP queries.
Utility Functions Exported utility functions / helpers.
`as.utf8()` `as.nativeEnc()` `as.corpusEnc()`	Conversion between corpus and native encoding.
`store()` `mail()` `browse()`	Defunct functionality
Backwards Compatibility Starting with v0.7.9, the coding style of the polmineR-package has moved from camelCase to snake_case. A set of ‘old style’-functions ensures backwards compatibility and that old code will not break.
`sAttributes()` `pAttributes()` `getTokenStream()` `getTerms()` `getEncoding()` `partitionBundle()` `as.partitionBundle()` `corpus(<textstat>)` `corpus(<bundle>)` `corpus(<kwic>)`	Renamed Functions

Reference

Package Basics

Corpora and subcorpora

Methods I: Basic Vocabulary

Methods II: Processing Objects

Methods III: Fulltext Output

The 'textstat' Class & Childs

The 'kwic' & 'Labels' Classes

The 'bundle' Class & Childs

Low-level CWB Access

Utility Functions

Backwards Compatibility